We are developing an adaptive reminding system, which learns when and how to present notifications. In this paper, we focus on our XCS-based model, composed of two cascaded sets ...
Domain adaptation is a fundamental learning problem where one wishes to use labeled data from one or several source domains to learn a hypothesis performing well on a different, y...
Artificial intelligence (AI) can contribute to the management of a data driven simulation system, in particular with regard to adaptive selection of data and refinement of the mo...
In this paper we present a novel approach to acoustic model training for non-audible murmur (NAM) recognition using normal speech data transformed into NAM data. NAM is extremely ...
Background: Different microarray studies have compiled gene lists for predicting outcomes of a range of treatments and diseases. These have produced gene lists that have little ov...
Gad Abraham, Adam Kowalczyk, Sherene Loi, Izhak Ha...